arXiv subjects

Georges Abboudeh

Publications and source records attributed to Georges Abboudeh.

3 recordsLinked to original sources

arXiv2026

What sets the star-formation rate in the Milky Way? I. A multi-scale view of the star-formation rate

Context. The star-formation rate (SFR) is one of the key quantities that characterizes the star formation process and has been extensively investigated both observationally and theoretically. Aims. We aim to provide a coherent multi-scale view of star formation by connecting Galactic-scale conditions (kpc) to the properties of individual star-forming clumps at sub-parsec scales. Methods. We perform a set of numerical simulations with large-scale turbulent forcing designed to reproduce physical conditions typical of the solar neighbourhood. Using adaptive zooming down to 0.03 pc, we obtain a population of star-forming clumps that is analyzed and compared with observational catalogues in a companion paper. Results. For column densities and velocity dispersions consistent with Galactic values, the resulting SFR is close to the rate inferred for the Milky Way. Comparing this value with the SFR expected from pure free-fall collapse shows that turbulence provides multiscale support that lowers the SFR by more than an order of magnitude. Additional regulation by stellar feedback, including ionizing radiation and protostellar outflows, likely reduces the SFR by an additional factor of 3-10. Comparisons with observations across multiple spatial scales show good overall agreement with this model. Conclusions. These results support a picture in which turbulence plays a central role in regulating star formation in the Milky Way. In combination with stellar feedback, it limits the star formation efficiency to only a few percent. Key words. stars: formation -- ISM: clouds -- physical processes: turbulence

astro-ph.GA↗

arXiv2026

What sets the star-formation rate in the Milky Way?. II. Comparing the star-forming clumps from simulations and observations

Context. Linking the star formation (SF) properties of dense clumps to their parent large-scale environment is a key step to interpret Galactic surveys. Achieving a consistent, multi-scale picture of SF requires a comparative analysis of observations and simulations. Aims. We exploit kiloparsec-scale magneto-hydrodynamic simulations designed to reproduce local Milky Way conditions. Leveraging the wide range of scales covered by the simulations (reaching a resolution of 0.03 pc), we aim to compare the properties of the simulated population of star-forming clumps with observational catalogues. Methods. After extracting the star-forming structures with the HOP clump-finding algorithm, we compare their physical (mass and size) and SF properties (SF rate and efficiency) with those of the Hi-GAL compact source catalogue. Results. Despite the different methodologies and the three-dimensional nature of our clump extraction, the simulated clumps show good agreement with the observed sample in their mass and size distributions. We discover a consistently linear relation between mass and SF rate (SFR) for the simulated clumps, which is remarkably independent of the initial conditions of the boxes. Using scaling relations to distinguish between turbulence- and gravity-regulated gas inflow onto the clump scales, we find tentative evidence in favour of a gravity-regulated regime of SF at the probed sub-parsec scales. Key words. methods: numerical - stars: formation - ISM: clouds

astro-ph.GA↗

arXiv2026

Are supernovae driving turbulence in the solar neighborhood?

Turbulence plays an important role in shaping the interstellar medium, and strongly influences star formation. We aim to identify the physical processes capable of sustaining HI turbulence in the solar neighborhood. We compare recent HI line-of-sight velocity observations within a volume of radius 70-500 pc centered on the Sun with a suite of 1 kpc numerical simulations that include two distinct turbulent drivers: (i) supernova (SN) feedback and (ii) imposed large-scale turbulent forcing. For each simulation, we construct synthetic sky maps that closely mimic the observational one, allowing for a consistent comparison between the simulations and the observational data. HI observations show a median velocity dispersion of 11.1 km s-1 in the solar neighborhood. SN-driven simulations systematically underpredict this value, yielding dispersions in the range 4.9-6.7 km s-1. Simulations with strong enough large-scale forcing can reproduce not only the median observed velocity dispersion, but also the observed velocity distribution.

astro-ph.GA↗